Fixed drone visualization in security systems

ABSTRACT

An unmanned aerial vehicle is described and includes a computer carried by the unmanned aerial vehicle to control flight of the unmanned aerial vehicle and at least one sensor. The unmanned aerial vehicle is caused to fly to a specific location within a facility, where the unmanned aerial vehicle enters a hover mode, where the unmanned aerial vehicle remains in a substantially fixed location hovering over the specific location within the facility and sends raw or processing results of sensor data from the sensor to a remote server system.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/274,066, filed Feb. 12, 2019, which is a continuation of U.S. patentapplication Ser. No. 14/516,671 filed Oct. 17, 2014, the entireties ofwhich are incorporated by reference herein.

BACKGROUND

This description relates to operation of security systems in particularsurveillance systems.

Conventionally, commercial surveillance systems were those that weremanned by humans that regularly traversed a facility checking in atguard stations and making observations. Surveillance systems progressedto include closed circuit television monitoring, and more recentlyintegrated systems have been developed to include video camerasinstalled at strategic locations in a facility. These video cameras arein communication with a centralized remote monitoring facility andoperators at the facility visually sweep the facility from themonitoring center. These tours are scripted and timed at a user request.Upon discovery of suspicious activity, the operator can engage in acustom designed response plan.

One surveillance solution has been employed by the military by the useof surveillance unmanned aerial vehicles, commonly referred to asdrones. Military surveillance drones are capable of flying oversubstantial areas such that video surveillance can be achieved. Militarysurveillance drones are very expensive and address surveillance of verylarge outdoor areas. However, these drones are not practical forbusinesses that want to maintain security at a single location or smallgroup of locations such as a warehouse or a manufacturing facility.

SUMMARY

The problem with conventional commercial types of surveillance systemsis that the systems require a significant investment in video cameras tocover all critical areas and are prone to missing conditions. Forexample, video surveillance systems covering large areas or spacerequire many cameras, large amount of media storage (local DVRs orremote hosting), video management tools to investigate the accumulatedinformation from all the cameras, and analytics for each of the manystreaming video channels from the many cameras. In most cases, licensingto operate the analytics is on a per channel basis. This applies to bothsystems that are completely wired and those that use some degree ofwireless technology.

On the other hand, military surveillance drones are very expensive andaddress surveillance of very large outdoor areas. Commercialapplications require a much more cost efficient solution. Limitations ofconventional commercial systems are significant causes of missedconditions, as well as false alarms that can cost alarm monitoringcompanies, building owners, security professionals and/or policedepartments significant amounts of money and wasted time that wouldotherwise be spent on real intrusion situations.

According to an aspect, a method includes sending by a computer to adrone a message to cause the drone to fly to a specific location withina facility, determining when the drone has reached the specificlocation, causing the drone to enter a hover mode, where the droneremains in a substantially fixed location hovering over the specificlocation within the facility, receiving sensor data from a sensorcarried by the drone, apply processing to the sensor data to detect anunacceptable level of detected feature differences in features containedin the sensor data at the location in the facility; and outputting anindication of unacceptable level of detected feature differences.

The following are some of the features within this aspect.

The method autonomously launches the drone from a drone station ondemand by reception of the message to the drone. The method causes thedrone to check by to the drone station within the facility when anindication is received to terminate the hover mode. The indication isreceived from a server or central monitoring station causing the droneto terminate the hover mode. The indication received is a signal thatindicates the drone needs refueling. The sensor data is captured by thedrone and compare with sensor data previously captured to determinewhether there exists the unacceptable level of detected featuredifferences.

According to an aspect, an unmanned aerial vehicle includes a computercarried by the unmanned aerial vehicle to control flight of the unmannedaerial vehicle, at least one sensor carried by the unmanned aerialvehicle, with the computer configured to cause the unmanned vehicle tofly to a specific location within a facility, determine when theunmanned aerial vehicle has reached the specific location, cause theunmanned aerial vehicle to enter a hover mode, where the unmanned aerialvehicle remains in a substantially fixed location hovering over thespecific location within the facility, receive sensor data from thesensor carried by the unmanned aerial vehicle, apply processing to thesensor data to detect an unacceptable level of detected featuredifferences in features contained in the sensor data at the location inthe facility, and output an indication of unacceptable level of detectedfeature differences to a remote server system.

Aspects of the invention include computer program products tangiblestored on a physical, hardware storage device or devices or systems.

The above techniques can include additional features and can provide oneor more of the following advantages.

The use of drones and analysis information provided by the drones wouldlikely significantly reduce the rate of false alarms while providingmore robust surveillance monitoring at lower costs than many currenttechniques. Reducing false alarms would likely minimize costs borne byalarm monitoring companies, building owners, and security professionals,and better utilize police department resources to handle real intrusionsituations.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention is apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an example surveillance system at afacility, according to some embodiments.

FIG. 1A is a schematic of a typical structure, according to someembodiments.

FIG. 2 is a block diagram of a surveillance system, according to someembodiments.

FIG. 3 is a flow diagram showing an example process for determiningsurveillance mapping, according to some embodiments.

FIG. 4 is a flow diagram of an analysis process, according to someembodiments.

DETAILED DESCRIPTION

Referring now to FIG. 1 , an example application 10 of a surveillancesystem 12 installed at a facility 14 is shown. In this example, thefacility 14 is, e.g., a commercial, industrial, facility, with interiorareas, 14 a (buildings) and exterior areas 14 b that are subject tosurveillance. The buildings 14 a can be of any configuration, wide openspaces such as a warehouse, to compartmentalized facilities such aslabs/offices. The surveillance system 12 includes one or more UAV ordrone stations 16 (for example, HATP's, discussed below). A UAV(unmanned aerial vehicle) commonly known as a drone is a remotelypiloted airborne vehicle, i.e., an aircraft that does not have a humanpilot aboard. However, a human controls the flight of the drone remotelyor in some applications the flight of the drone is controlledautonomously by onboard computers.

The drone stations 16 provide bases for one or more of the plural drones18. The system also includes a server 20 that is in communication withthe drones 18 and a gateway 22 to send data to and receive data from aremote, central monitoring station 24 (also referred to as centralmonitoring center) via one or more data or communication networks 26(only one shown), such as the Internet; the phone system or cellularcommunication system 25 being examples of others. The server 20 receivessignals from the plural drones. These signals include video signals fromonboard cameras as well as location information.

Referring to FIG. 1A an exemplary floor plan for an exemplary one of thebuildings 14 a is shown in some detail, including hallways, and officeswith various doorways, all shown schematically but not with referencenumbers. Also shown are fixed location markers 30 that can be any one ofa number of technologies, e.g., waypoints discussed below, the server20, gateway 22 and drone station 16 that is likewise a waypointdiscussed below.

The drones can carry several types of sensor/detectors. One type ofsensor is a video camera that sends video data to the server 20.Examples of other types of sensors 28 b include microphones to sendaudio data. The sensors 28 communicate wirelessly to the server 20 orcommunicate through an on-board computer on the drone. In general,sensors 28 a capture audio and video and send signals to the server 20.Based on the information received from the sensors 28 a, the server 20determines whether to trigger and/or send alarm messages to themonitoring station 18. An operator at the remote control stationcontrols actions of the drone.

The data or communication network 24 may include any combination ofwired and wireless links capable of carrying packet and/or switchedtraffic, and may span multiple carriers, and a wide geography. In oneembodiment, the data network 24 may simply be the public Internet. Inanother embodiment, the data network 24 may include one or more wirelesslinks, and may include a wireless data network, e.g., with tower 25 suchas a 2G, 3G, 4G or LTE cellular data network. Further networkcomponents, such as access points, routers, switches, DSL modems, andthe like possibly interconnecting the server 20 with the data network 24are not illustrated.

Referring now to FIG. 2 , details on an exemplary drone 18 are shown.The drone 18 includes processor 32 and memory 34, and storage 33 and awireless network interface card (NIC) 36 all coupled via a bus 42. Thedrone 18 also includes one or more sensors and one or more interfaces 38to receive sensor data from the sensors 28. Illustrated for explanatorypurpose are camera and microphone sensors 28 and interfaces 38 for thosesensors. The sensors 28 are coupled to the interfaces either via hardwiring or wirelessly. The drone 18 also includes flight controlelectronics and one or more electric motors to control one or morepropellers. The drone includes a body that can be either that of a planeor a helicopter. The drone flight control electronics are responsive tocontrol signals received by the processor via the wireless interfacecard that allow a remotely positioned operator to control flight of thedrone and control the camera and microphone on the drone.

Referring now to FIG. 3 , an alarm condition is asserted 51 within thefacility. In response to the alarm condition, the drone is autonomouslyprogrammed 52 by the server with a route that starts from the drone'sinitial location, typically a home station to a location where the alarmcondition was asserted. The drone in an autonomous manner flies to thatlocation in the building carrying sensors to gather sensor data that canbe in various forms such as live video that is sent back to the serverand onto the security monitoring center where the video is stored andviewed.

The drone is launched, and as the drone flies the programmed pattern itcollects such sensor data. However, the drone is programmed to fly to aparticular location within a facility. The drone or the serverdetermines 58 when the drone is at the specified location. Prior toarriving, (determination is “no”) the drone continues to send and theserver receives sensor data over the flight path. Once the drone arrivesat that specific location in the facility, the drone hovers 60 at thatlocation in the facility by entering a hover mode. The drone can becontrolled autonomously such that the camera is pointing to a locationof interest or at that point the drone can be controlled by an operator.The drone continually captures 62 sensor data, e.g., video. This data isstored and sent back to the operator for display on a display device. Atsome point the drone receives 64 a signal to return to base. The signalcan originate either from the operator (monitoring station) or theserver 20, an authorized client device (not shown) or the drone 18itself, as the drone would be monitoring its fuel supply or level ofremaining battery charge. In the latter situations of the signaloriginating from the server 20 or authorized client device or the drone18 itself, one of those devices would send a signal back to the operator(monitoring station) to indicate that the drone 18 is returning to base66 to allow another drone to be launched. Guidance within or outside ofa building can be accomplished by several techniques.

For example, when outside of a building, guidance can be accomplished byglobal position system (GPS) tracking. Alternative techniques include anoperator at the monitoring facility manually flying the drone to aspecific location or having the drone hover at the location. Within abuilding guidance can be accomplished by feature recognition to follow apreprogrammed map of the interior of the building. Another type ofnavigation is a map based type navigation that includes a database thatstores images of landmarks, descriptions of items and navigationinstructions. A third type of navigation is by r.f. (radio frequency)beacons being deployed within the facility, sending out r.f signals thata guidance system on board the drone captures and uses to apply atriangulation algorithm to figure out current location.

Within a building feature several guidance techniques whetherr.f.-based, sonar-based or optical-based, can be used.

Crash Avoidance:

The drone has crash avoidance systems that are used during flight todetect and record any physical objects that disrupt the ability of thedrone to follow a route plan. Many drones now come supplied with crashavoidance systems that determine proximity to nearby objects and areused with drone navigation to navigate around the object and return to apreprogramed path or route.

When establishing a route plan (RP), programmable waypoints placed,e.g., at location points, objects, locations, etc. along a pathdetermined by the plan that a drone will fly to in sequential orderwhile using crash avoidance capability to move along safely and intactbetween waypoints. The number of programmable routes is limited by theamount of onboard memory allocated for routes. If RPs are stored on aserver and delivered to the drone during flight, the number of waypointsis limited by the amount of server memory and processing power allocatedfor waypoints. The waypoints are small devices that are programmable andinclude an RF transmitter devices, e.g., RFID or low power RFtransmitters that continually broadcast its identity and/or placementand which are placed at locations where the asset being protected islocated and at all permitted points of entry to the protected area.

One type of waypoint is an Asset to Protect (ATP) waypoint. Thesewaypoints are a specific type of waypoint that is placed near the itemor area of high value and susceptible to attack or theft. Another typeof waypoint is Home Asset to Protect (HATP) waypoint. This is a specifictype of waypoint. This waypoint itself is a high value item, andsusceptible to attack or theft. It is the home for the drone where thedrone docks, recharges, and exchanges data with the server(s) the droneis associated with. The drone continually calculates how much power thedrone has for flying, how far away the drone is from a HATP, and thuscan calculate when to return to an HATP for recharging. Another type ofwaypoint is a Perimeter Point to Protect (PPP) waypoint. This is aspecific type of waypoint that are placed along perimeters along aroute. This waypoint is an item or area of high value and susceptible toattack or theft.

The Route Plan (RP) is a flight path that is developed and programmedinto the drone, by the server executing a flight service. The Route Planis established by the use of the aforementioned waypoints. The RoutePlan can be predefined for each HATP waypoint to each location ofinterest, i.e., ATP waypoint. These RP can be preloaded into the drone,memory permitting, or a single RP can be uploaded into the drone ondemand, based on a detected alarm condition by the server. Duringflight, the drone recognizes the existence of the waypoints and uses thewaypoints to navigate to and between waypoints. Using crash avoidancewhile traveling to a waypoint, the flight plan is established andrecorded. When flying the route, the drone uses crash avoidance todetermine and report any deviations from the already determine plan. Thedrone captures images of the deviation and reports them as troublesduring the premises disarmed period or alarm during the premises armedperiod.

A Triggered Alarm Response (TAR) is provided by the drone and serverthat contain the flight service programmed with the awareness of thedesired (normal non-alarm/trouble) condition of the environment isinterfaced to other security systems and/or services, i.e. IntrusionDetection System, Access Control, and Video Surveillance. The interfacecan be done through a predefined Application Programming Interface (API)using Web Services, XML, or proprietary formats. Through this interfaceand by input of the operator/user via a graphical user interface, theRoute Plan relative to the location of the waypoints knows the locationof the points of protection from the other connected alarm systems. Onany alarm or trouble that is initiated by an interconnected securitysystem, the drone uses the RP and crash avoidance to fly to the waypointclosest to the reported point of protection that triggered the alarm ortrouble to capture and transmit to the Home Asset to Protect (HATP)point(s) video images, sound, and temperature. This data is fed to a RPservice analytics engine for comparison to the normal non-alarm/troublecondition, and relayed to the command center and/or monitoring center.

More specifically, the drone navigates by the above mentioned waypointsprocessing captured signals from the various waypoints to recognize itscurrent position (e.g. stairs, exits, doors, corridors, etc.) within afacility. The drone has stored the flight plan that takes intoconsideration the relevant building or environment. Having thisinformation, the drone correlates captured signals to features in theflight plan. By correlating the captured signals to the features in theflight plan, the drone can determine its current waypoint, is providedinformation on that waypoint, and can navigate to a subsequent waypointbased on the flight plan. The drone may incorporate the functionality ofa compass to assist in navigation. In some implementations, theprocessing, rather than being performed by the drone, is performed bythe server and the server receives the signals, processes the signalsagainst the flight plan and the server sends navigation instructions tothe drone to control flight of the drone.

A flight plan is essentially a navigation map structure that is producedand includes paths between a starting waypoint and an ending waypoint.The navigation map is stored as a structure such as a graph datastructure that includes a set of nodes and a set of edges that establishrelationships (connections) between the nodes. A graph g is defined asfollows: g=(V, E), where V is a finite, non-empty set of vertices and Eis a set of edges (links between pairs of vertices). When the edges in agraph have no direction, the graph is called undirected, otherwise it iscalled directed. Information may be associated with each node and edgeof the graph. Each location or landmark corresponds to a waypoint and isrepresented as a node or vertex of the graph, and each description ordistance between two waypoints is represented as an edge or link betweenthe nodes. Associated with each edge is information that is in the formof flight instructions that control how the drone navigates from onenode to the next node, e.g., by including data on engine speed anddirection.

The edges correspond to relationships between the waypoints. Each edgehas information about connectedness to other waypoints and informationabout proximity of waypoints. Since each node generally has one or moreedges that connect to one or more nodes, a description of therelationship between nodes, such as navigation instructions for theflight electronics are obtained by accessing the data structure thatstores the information defining the relationships among the waypoints.

Referring now to FIG. 4 , the server 20 system and/or the centralmonitoring station receives 70 signals from various sensors e.g., acamera, a microphone, etc. on the drones. The server 20 applies 72analytics to the sensor data, e.g., the video, by comparing forinstance, current images captured by the drone at a particular locationto stored images previously taken at the same location to detectfeatures in the current images that are different than expected based onthe stored images.

In the case where an unacceptable level of feature differences isdetected 74 that could be an indication of detected movement of a personor thing, within the field of view of the images, the analytics outputsan indication. In the case where the server performs the processing, theserver 20 notifies the monitoring station or where the monitor station20 is performing the processing, monitoring station alerts the operator.Additional actions 78 can be taken by the server 20 and/or centralmonitor station 24, as a result of outputting the indication. Forexample, the processing upon detection of an unacceptable level offeature differences can signal launching of additional drones or for anintervention or modification of the hover position of the drone.

When the drone is in the autonomous mode, a modified flight pattern canbe accomplished by the server 20 producing a new flight pattern takinginto consideration results of analytics processing, and reprogrammingthe drone with the new flight pattern. Alternatively, the server 20 cancause flight control of the drone to be transferred to an operator. Theanalytics processing produces messages that are sent to a display (notshown) within view of the operator to assist the operator in guiding thedrone and thus apply a new flight pattern. The new flight pattern can bevaried including causing the drone to hover about that locationproviding continuous video surveillance back to the monitoring stationor to follow a path determined by the analytics processing.

The alarm condition discussed above can be detected by other sensorswithin a facility, such as a window being opened or a glass breakdetector or contact switch being asserted which are captured by anintrusion detection system (not shown). A drone at a Home Asset toProtect (HATP) waypoint is autonomously launched from the Home Asset toProtect (HATP) waypoint, by the server 20 that is also part of broaderintrusion detection system (not shown) to fly to that location providingconstant surveillance of the location until the incident is evaluatedand handled.

The drone, the server or the central monitor station can perform, partor all of the processing in FIGS. 3 and 4 .

The system includes a charging station HATP waypoint where drones landto recharge batteries (not shown) as needed. The drones are small,inexpensive devices that are programmed to fly a predetermined patternor to specific locations of interest within a building providing livevideo back to a security monitoring center.

Drone Characteristics:

Drones employed herein are selected according to the type and nature ofthe surveillance. For example, when the drones are employed to hover, ahelicopter type drone might be preferable to an airplane type drone. Inaddition, when deployed outdoors of the facility, the drones in generalcan be relatively large in comparison to those employed inside abuilding within the facility. Moreover, a drone employed within abuilding that has wide open spaces can be in general larger than oneemployed in a building that has many rooms and corridors. Thus, atypical wing span for a drone outside can be 1 to 5 feet, whereas insideit would likely be less than 1 foot. In addition, when used exclusivelyoutside the drone can be powered by a hydrocarbon, e.g., gas or gasolineengine, whereas inside the drone should be powered electrically, e.g.,fuel cell and/or batteries. These are however general considerations andspecific applications would govern actual implementations.

Various sensors can be carried by the drone, thus sensors includemicrophones to sense sound, and cameras to capture images and/or video.However, other sensors can include sensors to capture motion, vibration,pressure, heat, and so forth, in an appropriate combination to detect atrue condition in a facility.

The memory 34 stores program instructions and data used by theprocessor. The memory 34 may be a suitable combination of random accessmemory and read-only memory, and may host suitable program instructions(e.g. firmware or operating software), and configuration and operatingdata and may be organized as a file system or otherwise. The programinstructions stored in the memory may further store software componentsallowing network communications and establishment of connections to thedata network.

Program instructions stored in the memory along with configuration datamay control overall operation of drone.

An example monitoring station 18 can be a single physical monitoringstation or center in FIG. 1 . However, it could alternatively be formedof multiple monitoring centers/stations, each at a different physicallocation, and each in communication with the data network 24. Thecentral monitoring station 18 includes one or more monitoring server(s)82 each processing messages from the drones and/or user devices (notshown).

The monitoring server 82 may include a processor, a network interfaceand a memory (all not illustrated). The monitoring server 82 mayphysically take the form of a rack mounted card and may be incommunication with one or more operator terminals (not shown). Anexample monitoring server 82 is a SURGARD™ SG-System III Virtual, orsimilar system.

The processor of each monitoring server 82 acts as a controller for eachmonitoring server 82, and is in communication with, and controls overalloperation, of each server 82. The processor may include, or be incommunication with the memory that stores processor executableinstructions controlling the overall operation of the monitoring server82. Suitable software enable each monitoring server 82 to receive alarmsand cause appropriate actions to occur. Software may include a suitableInternet protocol (IP) stack and applications/clients.

Each monitoring server 82 of central monitoring station 18 may beassociated with an IP address and port(s) by which it communicates withthe control panels 16 and/or the user devices to handle alarm events,etc. The monitoring server address may be static, and thus alwaysidentify a particular one of monitoring server 32 to the intrusiondetection panels. Alternatively, dynamic addresses could be used, andassociated with static domain names, resolved through a domain nameservice. The network interface may be a conventional network interfacethat interfaces with the network 24 (FIG. 1 ) to receive incomingsignals, and may for example take the form of an Ethernet networkinterface card (NIC).

Servers can be any of a variety of computing devices capable ofreceiving information, such as a server, a distributed computing system10, a rack-mounted server and so forth. Server may be a single server ora group of servers that are at a same location or at differentlocations. Servers can receive information from client device userdevice via interfaces. Interfaces can be any type of interface capableof receiving information over a network, such as an Ethernet interface,a wireless networking interface, a fiber-optic networking interface, amodem, and so forth. Server also includes a processor and memory and abus system including, for example, an information bus and a motherboard,can be used to establish and to control information communicationbetween the components of server.

Processor may include one or more microprocessors. Generally, processormay include any appropriate processor and/or logic that is capable ofreceiving and storing information, and of communicating over a network(not shown). Memory can include a hard drive and a random access memorystorage device, such as a dynamic random access memory computer readablehardware storage devices and media and other types of non-transitorystorage devices.

Embodiments can be implemented in digital electronic circuitry, or incomputer hardware, firmware, software, or in combinations thereof.Computer programs can be implemented in a high-level procedural orobject oriented programming language, or in assembly or machine languageif desired; and in any case, the language can be a compiled orinterpreted language. Suitable processors include, by way of example,both general and special purpose microprocessors. Generally, a processorwill receive instructions and information from a read-only memory and/ora random access memory. Generally, a computer will include one or moremass storage devices for storing information files; such devices includemagnetic disks, such as internal hard disks and removable disks;magneto-optical disks; and optical disks. Hardware storage devicessuitable for tangibly embodying computer program instructions andinformation include all forms of non-volatile memory, including by wayof example semiconductor memory devices, such as EPROM, EEPROM, andflash memory devices; magnetic disks such as internal hard disks andremovable disks; magneto-optical disks; and CD ROM disks. Any of theforegoing can be supplemented by, or incorporated in, ASICs(application-specific integrated circuits).

Other embodiments are within the scope and spirit of the descriptionclaims. For example, due to the nature of software, functions describedabove can be implemented using software, hardware, firmware, hardwiring,or combinations of any of these. Another type of crash avoidance systemse.g., navigation is recognition-based guidance accomplished by applyingfeature recognition to follow a preprogrammed map of the interior of thebuilding. The map would be as a series of features extracted fromimages. The drone capture images during flight, applies featurerecognition to the images and extracts those recognized features andcompares recognized features to features in the map to adjust flightpaths, as needed within the building. Other embodiments are within thescope of the following claims.

1-7. (canceled)
 8. A method of aerial surveillance, comprising:receiving, by a computer system from a building management system (BMS),an alarm condition; programming, by the computer system, a drone with atleast a portion of a map including a route between a starting point anda location of interest, the map comprising a data structurerepresentation of a plurality of radio-frequency (RF) devices whereinthe drone navigates to the location of interest by determining itsposition on the route using signals from the plurality of RF devices;and sending, by the drone, to the computer system, sensor data inresponse to arriving at the location of interest.
 9. The method of claim8, wherein the drone further navigates using feature recognition. 10.The method of claim 8, comprising: the data structure representationcomprising a series of features extracted from images; and the droneadjusting the route based on applying feature recognition to the seriesof features, feature recognition comprising: capturing flight images;extracting recognized features from the flight images; and comparing therecognized features to the series of features of the map.
 11. The methodof claim 8, comprising: determining deviations from the route based on alocation of the drone; and reporting, by the drone, the deviations fromthe route to the computer system.
 12. The method of claim 8, comprising:updating the route based on a deviation.
 13. The method of claim 8,comprising: comparing, by the computer system, the sensor data from thedrone to previous sensor data; and sending, by the computer system, anindication to the building management system (BMS) in response todetermining a feature difference based on the comparison.
 14. The methodof claim 8, wherein each of the plurality of radio-frequency (RF)devices comprise one of: an asset-to-protect (ATP) waypoint, wherein anATP waypoint is associated with a physical entity, wherein the physicalentity comprises a person or an object; a home-asset-to-protect (HATP)waypoint, wherein the HATP waypoint is associated with a drone dockingstation; or a perimeter-point-to-protect (PPP) waypoint, wherein the PPPwaypoint is associated with an area.
 15. The method of claim 8,comprising: the data structure representation comprising a set of nodesand a set of edges, each of the set of nodes corresponding to one of theplurality of RF devices and the set of edges defining a relationshipbetween the set of nodes.
 16. The method of claim 8, comprising: thedata structure representation comprising a plurality of nodes and aplurality of edges, the plurality of edges comprising flightinstructions that control how the drone navigates from one node of theplurality of nodes to a next node.
 17. The method of claim 8,comprising: the data structure representation comprising a plurality ofnodes and a plurality of edges, the plurality of edges comprisinginformation about connectedness between the plurality of nodes and aboutproximity of the plurality of nodes.
 18. An aerial surveillance system,comprising: a plurality of radio-frequency (RF) devices; a computersystem configured to: generate a map that includes a path between astarting point and a location of interest, the map comprising a datastructure representation of the plurality of RF devices; and determine aroute comprising a portion of the map; and one or more drones configuredto: receive the portion of the map from the computer system; navigate tothe location of interest by determining a position on the route based onsignals from the plurality of RF devices; and send to the computersystem sensor data of the location of interest.
 19. The system of claim18, comprising: the one or more drones to navigate using crash featurerecognition.
 20. The system of claim 18, comprising: the data structurerepresentation comprising a series of features extracted from images;and the one or more drones to adjust the route based on applying featurerecognition to the series of features, the one or more drones to:capture flight images; extract recognized features from the flightimages; and compare the recognized features to the series of features ofthe map.
 21. The system of claim 18, comprising: the one or more dronesto determine deviations from the route based on the location, and reportthe deviations from the route to the computer system.
 22. The system ofclaim 18, comprising: the computer system to update the route based on adeviation.
 23. The system of claim 18, comprising: the computer systemto compare the sensor data from the drone to previous sensor data; andsend an indication to a building management system in response todetermining a feature difference based on the comparison.
 24. The systemof claim 18, comprising: the plurality of radio-frequency (RF) devicescomprise one of: an asset-to-protect (ATP) waypoint, wherein an ATPwaypoint is associated with a physical entity, wherein the physicalentity comprises a person or an object; a home-asset-to-protect (HATP)waypoint, wherein the HATP waypoint is associated with a drone dockingstation; or a perimeter-point-to-protect (PPP) waypoint, wherein the PPPwaypoint is associated with an area.
 25. The system of claim 18,comprising: the data structure representation comprising a set of nodesand a set of edges, each of the set of nodes corresponding to one of theplurality of RF devices and the set of edges defining a relationshipbetween the set of nodes.
 26. A navigation system for an indoor aerialsurveillance system comprising: a plurality of radio-frequency (RF)devices; and a computer system running a flight service, wherein theflight service is configured to: generate a data structurerepresentation of a path between a starting point and a location ofinterest, the data structure representation comprising the plurality ofRF devices and one or more routes between each of the plurality of RFdevices; update the data structure representation based on data receivedfrom one or more drones; send a route of the one or more routes to adrone of the one or more drones; and wherein the drone navigates to a RFdevice based on the route and determining its position based on signalsfrom the plurality of RF devices.
 27. The system of claim 26, whereineach of the plurality of radio-frequency (RF) devices comprise one of:an asset-to-protect (ATP) waypoint, wherein an ATP waypoint isassociated with a physical entity, wherein the physical entity comprisesa person or an object; a home-asset-to-protect (HATP) waypoint, whereinthe HATP waypoint is associated with a drone docking station; or aperimeter-point-to-protect (PPP) waypoint, wherein the PPP waypoint isassociated with an area.